You signed in with another tab or window. Reload to refresh your session.You signed out in another tab or window. Reload to refresh your session.You switched accounts on another tab or window. Reload to refresh your session.Dismiss alert
Get bun.lock files to work with Cloudflare Workers CI
Get bun.lock files to work with Cloudflare Workers CI
As of the time of this writing, Cloudflare Workers CI does not work with the newer text-based bun.lock file and instead requires a bun.lockb file to build your app via their CI system.
This usually manifests itself with the following error when trying to deploy your apps using a bun.lock file:
AGENTS.md Best Practices for AI Coding Assistants: Comprehensive Guide
AGENTS.md has emerged as the de facto open standard for guiding AI coding assistants, now adopted by over 20,000 repositories and formalized in August 2025 through collaboration between OpenAI, Google, Cursor, Factory, and Sourcegraph. This file acts as a "README for machines"—providing structured, technical context that helps AI assistants write better code from the start. For Python + AWS + Terraform projects, a well-crafted AGENTS.md dramatically reduces friction, ensuring generated code follows your conventions, uses the right tools, and adheres to security requirements.
What is AGENTS.md and why it matters
AGENTS.md is a dedicated Markdown file that complements, not replaces, README.md. While README targets human developers with project overviews and quick-start guides, AGENTS.md contains detailed technical instructions specifically for AI coding agents. Think of it as onboarding documentation for an AI team member: ex
A drop-in replacement chat template for google/gemma-4-31B-it tuned for open-source agentic coding harnesses.
This file contains hidden or bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
Remove cache and old extensions under "~/.vscode-server/" on your Linux server
If you often connect to your Linux server using VSCode, the "~/.vscode-server/" folder (and sometimes the ~/.cache/ folder too) can get very large because VSCode:
Does NOT clean its download cache after installing extensions;
Does NOT delete old extensions after updating them;
Does NOT remove old VSCode servers after installing a new version.
If your server storage space is limited, you might consider cleaning "~/.vscode-server/" (and ~/.cache/) regularly using the bash script I wrote.
Simply run the following command:
This file contains hidden or bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
This project values small, direct, understandable code.
Prefer the simplest implementation that solves the problem without creating downstream complexity. Simple does not mean simplistic. It means the shortest clear path from point A to point B, with the fewest moving parts required to keep the system correct, maintainable, and easy to reason about.
Avoid enterprise-style ceremony unless it is clearly justified by the problem.
A pattern for building personal knowledge bases using LLMs.
This is an idea file, it is designed to be copy pasted to your own LLM Agent (e.g. OpenAI Codex, Claude Code, OpenCode / Pi, or etc.). Its goal is to communicate the high level idea, but your agent will build out the specifics in collaboration with you.
The core idea
Most people's experience with LLMs and documents looks like RAG: you upload a collection of files, the LLM retrieves relevant chunks at query time, and generates an answer. This works, but the LLM is rediscovering knowledge from scratch on every question. There's no accumulation. Ask a subtle question that requires synthesizing five documents, and the LLM has to find and piece together the relevant fragments every time. Nothing is built up. NotebookLM, ChatGPT file uploads, and most RAG systems work this way.
"It is not possible to unreserve more products of <product name> than you have in stock"
Sometimes, the reserved_quantity on the stock.quant record for a product becomes out-of-sync with the sum of the reserved quantity in stock.move.lines for that product.